In wireless communication systems of today, such as WCDMA and other CDMA systems, control of the uplink load is very important. If the uplink load becomes too high, the system may become unstable and it becomes impossible for users to maintain their quality targets. This causes an uplink “power rush”, in which users repeatedly raise their transmit powers until they are transmitting at full transmit power in futile attempts of reaching a stable situation where all users have adequate quality.
Various radio resource management (RRM) algorithms have been developed in order to avoid the above situation. Such RRM algorithms act on load measurements to control the uplink load and for example include:    Admission control: if the load exceeds a certain limit, new users are denied access to the system, rather than jeopardizing the system stability.    Congestion control: in situations where overload still occurs, congestion control reduces the load by terminating connections.    Rate control: by reducing the transmission rates of one or several users, the system load can be controlled.    Scheduling: by explicitly granting individual users or groups of users permission to transmit, the load can be maintained at a predetermined level.
To execute these functions, the load must be known with sufficient accuracy. In CDMA systems in general and WCDMA systems in particular, the best measure of the uplink load is the so-called noise rise or Rise-over-Thermal (RoT), which is defined as:
                              η          =                                    I              tot                        N                          ,                            (                  Eq          .                                          ⁢          1                )            where Itot is the total received power and N is the power of the background noise. N includes thermal noise, man-made noise, e.g. noise generated by spark plugs, as well as adjacent channel interference. Itot includes the background noise N but also interference generated by mobile terminals, both within and outside a cell.
In order to estimate RoT, estimations of Itot and N are thus needed. Assuming that it is possible to measure Itot with sufficient accuracy, the problem is to estimate the background noise N. No method of actually separating the background noise from the interference of the mobiles is known. In view of this, at first thought the solution would be to measure N when there is no traffic in the system, for example at nighttime. However, the day and night noise power typically varies considerably. Man-made noise is for example generally present to a much higher extent at daytime and there may also be variations in the thermal noise due to daily temperature variations. Therefore, noise measurements made at nighttime may not be representative of the daytime background noise.
Thus, it would be desirable to instead measure the noise level when it is needed. In the prior art, it has been proposed to interrupt all uplink transmissions in the system for short periods of time in order to measure the background noise. However, such a solution is associated with a number of problems. Firstly; it requires that the system is synchronized, i.e. that all users and nodes share a common time reference. For example, in cdma2000 the base stations are synchronized and it is possible to instruct all mobiles to cease transmitting for a short period of time in order to measure the background noise. Other systems, including WCDMA, are not that accurately synchronized, and the silent periods would have to be too long to guarantee that all mobiles are silent at the same time. This would lead to an unacceptably large capacity loss, since no data can be transmitted during the silent periods. Thus, the solution with silent periods cannot be used in asynchronous systems, which is a major drawback.
Moreover, introducing silent periods may prove prohibitively complex even in a synchronous system. Standardization would be required in order to enable the silent periods. Still another drawback is that the transmission interruptions may impact the network performance such that the quality of service is degraded.
Accordingly, no satisfactory solution for background noise estimation or RoT estimation has been presented in conventional telecommunication systems and there is a considerable need for an improved noise estimation mechanism.